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Data Mining Algorithms in C++: Data Patterns and Algorithms for Modern Applications
Paperback
DatabasesProbability & StatisticsProgramming
ISBN13: 9781484233146
Publisher: Apress
Published: Dec 19 2017
Pages: 286
Weight: 1.17
Height: 0.64 Width: 7.00 Depth: 10.00
Language: English
What You'll Learn
- Use Monte-Carlo permutation tests to provide statistically sound assessments of relationships present in your data
- Discover how combinatorially symmetric cross validation reveals whether your model has true power or has just learned noise by overfitting the data
- Work with feature weighting as regularized energy-based learning to rank variables according to their predictive power when there is too little data for traditional methods
- See how the eigenstructure of a dataset enables clustering of variables into groups that exist only within meaningful subspaces of the data
- Plot regions of the variable space where there is disagreement between marginal and actual densities, or where contribution to mutual information is high
Who This Book Is For Anyone interested in discovering and exploiting relationships among variables. Although all code examples are written in C++, the algorithms are described in sufficient detail that they can easily be programmed in any language.
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